{ggplot2} Essentials

class: center, middle, inverse, title-slide

# {ggplot2} Essentials

---

layout: true
  
<div class="dk-footer">
<span>
<a href="https://rfortherestofus.com/" target="_blank">R for the Rest of Us
</a>
</span>
</div>

---

class: center, middle, dk-section-title
background-image:url("images/pexels-photo-5282585.jpeg")
background-size: cover

# {ggplot2} essentials

---

### What is `{ggplot2}`?

`{ggplot2}` implements a *grammar of graphics* for building charts.

We can use it to consistently build **any**<sup>1</sup> chart.

![](data:image/png;base64,#02_01_ggplot2-essentials_files/figure-html/unnamed-chunk-3-1.png)

.footnote[
[1] - Dual y-axis charts must be transformations of one another ([for good reasons](https://stackoverflow.com/a/3101876/1659890))
]

---

# Building blocks of a {ggplot2} chart

- <svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#c03728;overflow:visible;position:relative;"><path d="M160 288h-56c-4.42 0-8-3.58-8-8v-16c0-4.42 3.58-8 8-8h56v-64h-56c-4.42 0-8-3.58-8-8v-16c0-4.42 3.58-8 8-8h56V96h-56c-4.42 0-8-3.58-8-8V72c0-4.42 3.58-8 8-8h56V32c0-17.67-14.33-32-32-32H32C14.33 0 0 14.33 0 32v448c0 2.77.91 5.24 1.57 7.8L160 329.38V288zm320 64h-32v56c0 4.42-3.58 8-8 8h-16c-4.42 0-8-3.58-8-8v-56h-64v56c0 4.42-3.58 8-8 8h-16c-4.42 0-8-3.58-8-8v-56h-64v56c0 4.42-3.58 8-8 8h-16c-4.42 0-8-3.58-8-8v-56h-41.37L24.2 510.43c2.56.66 5.04 1.57 7.8 1.57h448c17.67 0 32-14.33 32-32v-96c0-17.67-14.33-32-32-32z"/></svg> <span style='color:#c03728'>Aesthetics</span>

- <svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#919c4c;overflow:visible;position:relative;"><path d="M128,256A128,128,0,1,0,256,384,128,128,0,0,0,128,256Zm379-54.86L400.07,18.29a37.26,37.26,0,0,0-64.14,0L229,201.14C214.76,225.52,232.58,256,261.09,256H474.91C503.42,256,521.24,225.52,507,201.14ZM480,288H320a32,32,0,0,0-32,32V480a32,32,0,0,0,32,32H480a32,32,0,0,0,32-32V320A32,32,0,0,0,480,288Z"/></svg> <span style='color:#919c4c'>Geoms</span>

- <svg aria-hidden="true" role="img" viewBox="0 0 640 512" style="height:1em;width:1.25em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#fd8f24;overflow:visible;position:relative;"><path d="M256 336h-.02c0-16.18 1.34-8.73-85.05-181.51-17.65-35.29-68.19-35.36-85.87 0C-2.06 328.75.02 320.33.02 336H0c0 44.18 57.31 80 128 80s128-35.82 128-80zM128 176l72 144H56l72-144zm511.98 160c0-16.18 1.34-8.73-85.05-181.51-17.65-35.29-68.19-35.36-85.87 0-87.12 174.26-85.04 165.84-85.04 181.51H384c0 44.18 57.31 80 128 80s128-35.82 128-80h-.02zM440 320l72-144 72 144H440zm88 128H352V153.25c23.51-10.29 41.16-31.48 46.39-57.25H528c8.84 0 16-7.16 16-16V48c0-8.84-7.16-16-16-16H383.64C369.04 12.68 346.09 0 320 0s-49.04 12.68-63.64 32H112c-8.84 0-16 7.16-16 16v32c0 8.84 7.16 16 16 16h129.61c5.23 25.76 22.87 46.96 46.39 57.25V448H112c-8.84 0-16 7.16-16 16v32c0 8.84 7.16 16 16 16h416c8.84 0 16-7.16 16-16v-32c0-8.84-7.16-16-16-16z"/></svg> <span style='color:#919c4c'>Scales</span>

- <svg aria-hidden="true" role="img" viewBox="0 0 640 512" style="height:1em;width:1.25em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#f5c04a;overflow:visible;position:relative;"><path d="M497.941 225.941L286.059 14.059A48 48 0 0 0 252.118 0H48C21.49 0 0 21.49 0 48v204.118a48 48 0 0 0 14.059 33.941l211.882 211.882c18.744 18.745 49.136 18.746 67.882 0l204.118-204.118c18.745-18.745 18.745-49.137 0-67.882zM112 160c-26.51 0-48-21.49-48-48s21.49-48 48-48 48 21.49 48 48-21.49 48-48 48zm513.941 133.823L421.823 497.941c-18.745 18.745-49.137 18.745-67.882 0l-.36-.36L527.64 323.522c16.999-16.999 26.36-39.6 26.36-63.64s-9.362-46.641-26.36-63.64L331.397 0h48.721a48 48 0 0 1 33.941 14.059l211.882 211.882c18.745 18.745 18.745 49.137 0 67.882z"/></svg> <span style='color:#919c4c'>Guides</span>

---

# Building blocks of a {ggplot2} chart

---

# Building blocks of a {ggplot2} chart

- <svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#919c4c;overflow:visible;position:relative;"><path d="M128,256A128,128,0,1,0,256,384,128,128,0,0,0,128,256Zm379-54.86L400.07,18.29a37.26,37.26,0,0,0-64.14,0L229,201.14C214.76,225.52,232.58,256,261.09,256H474.91C503.42,256,521.24,225.52,507,201.14ZM480,288H320a32,32,0,0,0-32,32V480a32,32,0,0,0,32,32H480a32,32,0,0,0,32-32V320A32,32,0,0,0,480,288Z"/></svg> <span style='color:#919c4c'>Geoms</span>: these use the aesthetics to draw layers onto our charts

---

# Geoms & categorical variables

In R we use `factors` to control the order in which geoms are drawn (and appear in legends)

.pull-left[

- Default (alphabetical) ordering

<img src="data:image/png;base64,#02_01_ggplot2-essentials_files/figure-html/unnamed-chunk-4-1.png" width="100%" />
]

.pull-right[

- Reordered by another column

<img src="data:image/png;base64,#02_01_ggplot2-essentials_files/figure-html/unnamed-chunk-5-1.png" width="100%" />
]

---

# Building blocks of a {ggplot2} chart

- <svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#919c4c;overflow:visible;position:relative;"><path d="M128,256A128,128,0,1,0,256,384,128,128,0,0,0,128,256Zm379-54.86L400.07,18.29a37.26,37.26,0,0,0-64.14,0L229,201.14C214.76,225.52,232.58,256,261.09,256H474.91C503.42,256,521.24,225.52,507,201.14ZM480,288H320a32,32,0,0,0-32,32V480a32,32,0,0,0,32,32H480a32,32,0,0,0,32-32V320A32,32,0,0,0,480,288Z"/></svg> <span style='color:#919c4c'>Geoms</span>

---

# Building blocks of a {ggplot2} chart

- <svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#919c4c;overflow:visible;position:relative;"><path d="M128,256A128,128,0,1,0,256,384,128,128,0,0,0,128,256Zm379-54.86L400.07,18.29a37.26,37.26,0,0,0-64.14,0L229,201.14C214.76,225.52,232.58,256,261.09,256H474.91C503.42,256,521.24,225.52,507,201.14ZM480,288H320a32,32,0,0,0-32,32V480a32,32,0,0,0,32,32H480a32,32,0,0,0,32-32V320A32,32,0,0,0,480,288Z"/></svg> <span style='color:#919c4c'>Geoms</span>

- <svg aria-hidden="true" role="img" viewBox="0 0 640 512" style="height:1em;width:1.25em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#f5c04a;overflow:visible;position:relative;"><path d="M497.941 225.941L286.059 14.059A48 48 0 0 0 252.118 0H48C21.49 0 0 21.49 0 48v204.118a48 48 0 0 0 14.059 33.941l211.882 211.882c18.744 18.745 49.136 18.746 67.882 0l204.118-204.118c18.745-18.745 18.745-49.137 0-67.882zM112 160c-26.51 0-48-21.49-48-48s21.49-48 48-48 48 21.49 48 48-21.49 48-48 48zm513.941 133.823L421.823 497.941c-18.745 18.745-49.137 18.745-67.882 0l-.36-.36L527.64 323.522c16.999-16.999 26.36-39.6 26.36-63.64s-9.362-46.641-26.36-63.64L331.397 0h48.721a48 48 0 0 1 33.941 14.059l211.882 211.882c18.745 18.745 18.745 49.137 0 67.882z"/></svg> <span style='color:#919c4c'>Guides</span>: these affect how the guides (or legends) are constructed from the aesthetics and scales.

---

# Guides and maps

---

# Building blocks of a {ggplot2} chart

- <svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#919c4c;overflow:visible;position:relative;"><path d="M128,256A128,128,0,1,0,256,384,128,128,0,0,0,128,256Zm379-54.86L400.07,18.29a37.26,37.26,0,0,0-64.14,0L229,201.14C214.76,225.52,232.58,256,261.09,256H474.91C503.42,256,521.24,225.52,507,201.14ZM480,288H320a32,32,0,0,0-32,32V480a32,32,0,0,0,32,32H480a32,32,0,0,0,32-32V320A32,32,0,0,0,480,288Z"/></svg> <span style='color:#919c4c'>Geoms</span>

- <svg aria-hidden="true" role="img" viewBox="0 0 640 512" style="height:1em;width:1.25em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#f5c04a;overflow:visible;position:relative;"><path d="M497.941 225.941L286.059 14.059A48 48 0 0 0 252.118 0H48C21.49 0 0 21.49 0 48v204.118a48 48 0 0 0 14.059 33.941l211.882 211.882c18.744 18.745 49.136 18.746 67.882 0l204.118-204.118c18.745-18.745 18.745-49.137 0-67.882zM112 160c-26.51 0-48-21.49-48-48s21.49-48 48-48 48 21.49 48 48-21.49 48-48 48zm513.941 133.823L421.823 497.941c-18.745 18.745-49.137 18.745-67.882 0l-.36-.36L527.64 323.522c16.999-16.999 26.36-39.6 26.36-63.64s-9.362-46.641-26.36-63.64L331.397 0h48.721a48 48 0 0 1 33.941 14.059l211.882 211.882c18.745 18.745 18.745 49.137 0 67.882z"/></svg> <span style='color:#f5c04a'>Guides</span>

- <svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:#e68c7c;overflow:visible;position:relative;"><path d="M416 128V32c0-17.67-14.33-32-32-32H32C14.33 0 0 14.33 0 32v96c0 17.67 14.33 32 32 32h352c17.67 0 32-14.33 32-32zm32-64v128c0 17.67-14.33 32-32 32H256c-35.35 0-64 28.65-64 64v32c-17.67 0-32 14.33-32 32v128c0 17.67 14.33 32 32 32h64c17.67 0 32-14.33 32-32V352c0-17.67-14.33-32-32-32v-32h160c53.02 0 96-42.98 96-96v-64c0-35.35-28.65-64-64-64z"/></svg> <span style='color:#e68c7c'>Theme</span>: this affects the look and feel of the chart.

---

# {ggspatial}

The `{ggspatial}` package extends `{ggplot2}`'s mapping capabilities in three big ways:

- It allows us to add map tiles to maps

```
## 
  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |==                                                                    |   3%
  |                                                                            
  |=====                                                                 |   7%
  |                                                                            
  |=======                                                               |  10%
  |                                                                            
  |=========                                                             |  13%
  |                                                                            
  |============                                                          |  17%
  |                                                                            
  |==============                                                        |  20%
  |                                                                            
  |================                                                      |  23%
  |                                                                            
  |===================                                                   |  27%
  |                                                                            
  |=====================                                                 |  30%
  |                                                                            
  |=======================                                               |  33%
  |                                                                            
  |==========================                                            |  37%
  |                                                                            
  |============================                                          |  40%
  |                                                                            
  |==============================                                        |  43%
  |                                                                            
  |=================================                                     |  47%
  |                                                                            
  |===================================                                   |  50%
  |                                                                            
  |=====================================                                 |  53%
  |                                                                            
  |========================================                              |  57%
  |                                                                            
  |==========================================                            |  60%
  |                                                                            
  |============================================                          |  63%
  |                                                                            
  |===============================================                       |  67%
  |                                                                            
  |=================================================                     |  70%
  |                                                                            
  |===================================================                   |  73%
  |                                                                            
  |======================================================                |  77%
  |                                                                            
  |========================================================              |  80%
  |                                                                            
  |==========================================================            |  83%
  |                                                                            
  |=============================================================         |  87%
  |                                                                            
  |===============================================================       |  90%
  |                                                                            
  |=================================================================     |  93%
  |                                                                            
  |====================================================================  |  97%
  |                                                                            
  |======================================================================| 100%
```
</center>

---

# {ggspatial}

The `{ggspatial}` package extends `{ggplot2}`'s mapping capabilities in three big ways:

- It allows us to add map tiles to maps

- It allows us to add `{raster}` and `{terra}` datasets to `{ggplot2}` charts

- It allows us to add map-specific chart furniture to `{ggplot2}` charts